Status and trends of TMS research in depressive disorder: a bibliometric and visual analysis.

Depression is a chronic psychiatric condition that places significant burdens on individuals, families, and societies. The rapid evolution of non-invasive brain stimulation techniques has facilitated the extensive clinical use of Transcranial Magnetic Stimulation (TMS) for depression treatment. In light of the substantial recent increase in related research, this study aims to employ bibliometric methods to systematically review the global research status and trends of TMS in depression, providing a reference and guiding future studies in this field. We retrieved literature on TMS and depression published between 1999 and 2023 from the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) databases within the Web of Science Core Collection (WoSCC). Bibliometric analysis was performed using VOSviewer and CiteSpace software to analyze data on countries, institutions, authors, journals, keywords, citations, and to generate visual maps. A total of 5,046 publications were extracted covering the period from 1999 to 2023 in the field of TMS and depression. The publication output exhibited an overall exponential growth trend. These articles were published across 804 different journals, BRAIN STIMULATION is the platform that receives the most articles in this area. The literature involved contributions from over 16,000 authors affiliated with 4,573 institutions across 77 countries. The United States contributed the largest number of publications, with the University of Toronto and Daskalakis ZJ leading as the most prolific institution and author, respectively. Keywords such as "Default Mode Network," "Functional Connectivity," and "Theta Burst" have recently garnered significant attention. Research in this field primarily focuses on TMS stimulation patterns, their therapeutic efficacy and safety, brain region and network mechanisms under combined brain imaging technologies, and the modulation effects of TMS on brain-derived neurotrophic factor (BDNF) and neurotransmitter levels. In recent years, TMS therapy has demonstrated extensive potential applications and significant implications for the treatment of depression. Research in the field of TMS for depression has achieved notable progress. Particularly, the development of novel TMS stimulation patterns and the integration of TMS therapy with multimodal techniques and machine learning algorithms for precision treatment and investigation of brain network mechanisms have emerged as current research hotspots.

Yang J ，Tang T ，Gui Q ，Zhang K ，Zhang A ，Wang T ，Yang C ，Liu X ，Sun N ... -  《Frontiers in Psychiatry》

Bibliometric and visual analysis of transcranial direct current stimulation in the web of science database from 2000 to 2022 via CiteSpace.

This study aimed to evaluate the current research hotspots and development tendency of Transcranial Direct Current Stimulation (tDCS) in the field of neurobiology from a bibliometric perspective by providing visualized information to scientists and clinicians. Publications related to tDCS published between 2000 and 2022 were retrieved from the Web of Science Core Collection (WOSCC) on May 5, 2022. Bibliometric features including the number of publications and citations, citation frequency, H-index, journal impact factors, and journal citation reports were summarized using Microsoft Office Excel. Co-authorship, citation, co-citation, and co-occurrence analyses among countries, institutions, authors, co-authors, journals, publications, references, and keywords were analyzed and visualized using CiteSpace (version 6.1.R3). A total of 4,756 publications on tDCS fulfilled the criteria we designed and then were extracted from the WOSCC. The United States (1,190 publications, 25.02%) and Harvard University (185 publications, 3.89%) were the leading contributors among all the countries and institutions, respectively. NITSCHE MA and FREGNI F, two key researchers, have made great achievements in tDCS. Brain Stimulation (306 publications) had the highest number of publications relevant to tDCS and the highest number of citations (4,042 times). In terms of potential hotspots, we observed through reference co-citation analysis timeline viewer related to tDCS that "depression"#0, "Sensorimotor network"#10, "working memory"#11, and "Transcranial magnetic stimulation"#9 might be the future research hotspots, while keywords with the strong burst and still ongoing were "intensity" (2018-2022), "impairment" (2020-2022), "efficacy" (2020-2022), and "guideline" (2020-2022). This was the first-ever study of peer-reviewed publications relative to tDCS using several scientometric and visual analytic methods to quantitatively and qualitatively reveal the current research status and trends in the field of tDCS. Through the bibliometric method, we gained an in-depth understanding of the current research status and development trend on tDCS. Our research and analysis results might provide some practical sources for academic scholars and clinicians.

Sun W ，Song J ，Dong X ，Kang X ，He B ，Zhao W ，Li Z ，Feng Z ，Chen X ... -  《Frontiers in Human Neuroscience》

A bibliometric analysis of global research status and trends in neuromodulation techniques in the treatment of autism spectrum disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disease which has risen to become the main cause of childhood disability, placing a heavy burden on families and society. To date, the treatment of patients with ASD remains a complicated problem, for which neuromodulation techniques are a promising solution. This study analyzed the global research situation of neuromodulation techniques in the treatment of ASD from 1992 to 2022, aiming to explore the global research status and frontier trends in this field. The Web of Science (WoS) was searched for literature related to neuromodulation techniques for ASD from 1992 to October 2022. A knowledge atlas to analyze collaboration among countries, institutions, authors, publishing journals, reference co-citation patterns, keyword co-occurrence, keyword clustering, and burst keywords was constructed using Rstudio software, CiteSpace, and VOSviewer. In total, 392 publications related to the treatment of ASD using neuromodulation techniques were included. Despite some fluctuations, the number of publications in this field has shown a growing trend in recent years. The United States and Deakin University are the leading country and institution in this field, respectively. The greatest contributing authors are Peter G Enticott, Manuel F Casanova, and Paul B Fitzgerald et al. The most prolific and cited journal is Brain Stimulation and the most commonly co-cited journal is The Journal of Autism and Developmental Disorders. The most frequently cited article was that of Simone Rossi (Safety, ethical considerations, and application guidelines for the use of transverse magnetic stimulation in clinical practice and research, 2009). "Obsessive-compulsive disorder," "transcranial direct current stimulation," "working memory," "double blind" and "adolescent" were identified as hotspots and frontier trends of neuromodulation techniques in the treatment of ASD. The application of neuromodulation techniques for ASD has attracted the attention of researchers worldwide. Restoring the social ability and improving the comorbid symptoms in autistic children and adults have always been the focus of research. Neuromodulation techniques have demonstrated significant advantages and effects on these issues. Transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) are new therapeutic methods introduced in recent years, and are also directions for further exploration.

Xiao L ，Huo X ，Wang Y ，Li W ，Li M ，Wang C ，Wang F ，Sun T ... -  《BMC Psychiatry》

Research hotspots and trends of transcranial magnetic stimulation in Parkinson's disease: a bibliometric analysis.

Transcranial magnetic stimulation (TMS), as a non-invasive neuromodulation technique, has been widely used in the treatment of Parkinson's disease (PD). The increasing application of TMS has promoted an increasing number of clinical studies. In this paper, a bibliometric analysis of existing studies was conducted to reveal current research hotspots and guide future research directions. Relevant articles and reviews were obtained from the Science Citation Index Expanded of Web of Science Core Collection database. Data related to publications, countries, institutions, authors, journals, citations, and keywords in the studies included in the review were systematically analyzed using VOSviewer 1.6.18 and Citespace 6.2.4 software. A total of 1,894 papers on the topic of TMS in PD between 1991 and 2022 were analyzed and visualized to identify research hotspots and trends in the field. The number of annual publications in this field of study has increased gradually over the past 30 years, with the number of annual publications peaking in 2022 (n = 150). In terms of publications and total citations, countries, institutions, and authors from North America and Western Europe were found to make significant contributions to the field. The current hotspot focuses on the effectiveness of TMS for PD in different stimulation modes or different stimulated brain regions. The keyword analysis indicates that the latest research is oriented to the mechanism study of TMS for motor symptoms in PD, and the non-motor symptoms are also receiving more attention. Our study offers insights into the current hotspots and emerging trends of TMS in the rehabilitation of PD. These findings may serve as a guide for future research and the application of TMS for PD.

Wei YX ，Tu LD ，He L ，Qiu YT ，Su W ，Zhang L ，Ma RT ，Gao Q ... -  《Frontiers in Neuroscience》

Research Trends in the Application of Artificial Intelligence in Oncology: A Bibliometric and Network Visualization Study.

The past decade has seen major advances in the use of artificial intelligence (AI) to solve various biomedical problems, including cancer. This has resulted in more than 6000 scientific papers focusing on AI in oncology alone. The expansiveness of this research area presents a challenge to those seeking to understand how it has developed. A scientific analysis of AI in the oncology literature is therefore crucial for understanding its overall structure and development. This may be addressed through bibliometric analysis, which employs computational and visual tools to identify research activity, relationships, and expertise within large collections of bibliographic data. There is already a large volume of research data regarding the development of AI applications in cancer research. However, there is no published bibliometric analysis of this topic that offers comprehensive insights into publication growth, co-citation networks, research collaboration, and keyword co-occurrence analysis for technological trends involving AI across the entire spectrum of oncology research. The purpose of this study is to investigate documents published during the last decade using bibliometric indicators and network visualization. This will provide a detailed assessment of global research activities, key themes, and AI trends over the entire breadth of the oncology field. It will also specifically highlight top-performing authors, organizations, and nations that have made major contributions to this research domain, as well as their interactions via network collaboration maps and betweenness centrality metric. This study represents the first global investigation of AI covering the entire cancer field and using several validated bibliometric techniques. It should provide valuable reference material for reorienting this field and for identifying research trajectories, topics, major publications, and influential entities including scholars, institutions, and countries. It will also identify international collaborations at three levels: micro (that of an individual researcher), meso (that of an institution), and macro (that of a country), in order to inform future lines of research. The Science Citation Index Expanded from the Web of Science Core Collection was searched for articles and reviews pertaining exclusively to AI in cancer from 2012 through 2022. Annual publication trends were plotted using Microsoft Excel 2019. CiteSpace and VOSViewer were used to investigate the most productive countries, researchers, journals, as well as the sharing of resources, intellectual property, and knowledge base in this field, along with the co-citation analysis of references and keywords. A total of 6757 documents were retrieved. China produced the most publications of any country (2087, 30.89%), and Sun Yat Sen University the highest number (167, 2.47%) of any institute. WEI WANG was the most prolific author (33, 0.49%). RUI ZHANG ranked first for highest betweenness centrality (0.21) and collaboration criteria. Scientific Reports was found to be the most prolific journal (208, 3.18%), while PloS one had the most co-citations (2121, 1.55%). Strong and ongoing citation bursts were found for keywords such as "tissue microarray", "tissue segmentation", and "artificial neural network". Deep learning currently represents one of the most cutting-edge and applicable branches of AI in oncology. The literature to date has dealt extensively with radiomics, genomics, pathology, risk stratification, lesion detection, and therapy response. Current hot topics identified by our analysis highlight the potential application of AI in radiomics and precision oncology.

Wu T ，Duan Y ，Zhang T ，Tian W ，Liu H ，Deng Y ... -  《-》